Pickl AI

APRIL 26, 2024

Top 50+ Interview Questions for Data Analysts Technical Questions SQL Queries What is SQL, and why is it necessary for data analysis? SQL stands for Structured Query Language, essential for querying and manipulating data stored in relational databases. The mode is the value that appears most frequently in a data set.

Data Analyst 52

Data Analyst Data Analysis Data Analysis Machine Learning 52

Pickl AI

NOVEMBER 2, 2023

A cheat sheet for Data Scientists is a concise reference guide, summarizing key concepts, formulas, and best practices in Data Analysis, statistics, and Machine Learning. Here, we’ll explore why Data Science is indispensable in today’s world. Is Data Scientist math heavy?

Data Scientist 52

Data Scientist Data Science Data Visualization Machine Learning 52

PyImageSearch

DECEMBER 12, 2022

Setting Up the Prerequisites Building the Model Assessing the Model Summary Citation Information Scaling Kaggle Competitions Using XGBoost: Part 2 In our previous tutorial , we went through the basic foundation behind XGBoost and learned how easy it was to incorporate a basic XGBoost model into our project. Table 1: The Dataset.

Decision Trees 52

Decision Trees Deep Learning Deep Learning Exploratory Data Analysis 52

Dataconomy

AUGUST 9, 2023

But as in every aspect of our lives, Machine Learning algorithms and artificial intelligence help us in network traffic analysis. How could machine learning be used in network traffic analysis?

Machine Learning 91

Machine Learning Machine Learning ML ML 91

PyImageSearch

JANUARY 23, 2023

The reasoning behind that is simple; whatever we have learned till now, be it adaptive boosting, decision trees, or gradient boosting, have very distinct statistical foundations which require you to get your hands dirty with the math behind them. The goal is to nullify the abstraction created by packages as much as possible.

Deep Learning 107

Deep Learning Deep Learning Algorithm Decision Trees 107

IBM Journey to AI blog

DECEMBER 19, 2023

The challenge for IT departments working in data science is making sense of expanding and ever-changing data points. The main difference being that while KNN makes assumptions based on data points that are closest together, LOF uses the points that are furthest apart to draw its conclusions.

Machine Learning 66

Machine Learning Machine Learning Supervised Learning K-nearest Neighbors 66

Mlearning.ai

MAY 23, 2023

The following Venn diagram depicts the difference between data science and data analytics clearly: 3. Data analysis can not be done on a whole volume of data at a time especially when it involves larger datasets. Overfitting: The model performs well only for the sample training data.

Data Science 52

Data Science Decision Trees Machine Learning Machine Learning 52

IBM Journey to AI blog

JULY 6, 2023

Data science solves a business problem by understanding the problem, knowing the data that’s required, and analyzing the data to help solve the real-world problem. What is machine learning? It requires data science tools to first clean, prepare and analyze unstructured big data.

Machine Learning 56

Machine Learning Machine Learning Data Science Big Data 56

Mlearning.ai

FEBRUARY 15, 2023

Some important things that were considered during these selections were: Random Forest : The ultimate feature importance in a Random forest is the average of all decision tree feature importance. A random forest is an ensemble classifier that makes predictions using a variety of decision trees. link] Ganaie, M.

Cross Validation 52

Cross Validation Decision Trees Natural Language Processing Algorithm 52

Heartbeat

FEBRUARY 8, 2023

Natural Language Processing (NLP) plays a crucial role in advancing research in various fields, such as computational linguistics, computer science, and artificial intelligence. R is frequently used for statistical software development, data analysis, and data visualisation because it can handle large data sets with ease.

Natural Language Processing 52

Natural Language Processing Machine Learning Machine Learning Deep Learning 52

Heartbeat

MAY 29, 2023

It is therefore important to carefully plan and execute data preparation tasks to ensure the best possible performance of the machine learning model. Batch size and learning rate are two important hyperparameters that can significantly affect the training of deep learning models, including LLMs.

Machine Learning 78

Machine Learning Machine Learning Natural Language Processing Data Preparation 78